One technique in the field of data loss prevention is to categorize data available on a system, particularly by identifying sensitive data which might be the target of malicious activity. However, even when automated methods for categorizing and identifying sensitive data exist, users are reluctant to engage in the significant time and resources necessary to carry out the automated processes on large data sets.
In view of the foregoing, it may be understood that there may be significant problems and shortcomings associated with current data loss prevention techniques.